The numpy.frombuffer() function of the Numpy library is used to create an array by using the specified buffer.
This function interprets a buffer as a 1-dimensional array.
Syntax of frombuffer():
Given below is the required syntax that is used for numpy.frombuffer() function:
numpy.frombuffer(buffer, dtype, count, offset) Parameters:
Let us discuss the parameters of the above constructor:
- buffer
This parameter is used to represent an object that exposes a buffer interface. - dtype
This parameter is used to represent the data type of the returned data type array. The default value of this parameter is 0. - count
This parameter represents the length of the returned ndarray. The default value of this parameter is -1. - offset
This parameter indicates the starting position to read from. The default value of this parameter is 0.
Let us now discuss some examples using frombuffer() function.
Basic Example:
Below we have the code snippet in order to understand the working of this function:
import numpy as np
input = b'Welcome to ShishirKant!!!It is a best place for you to learn coding online..'
print("The type of input is:")
print(type(input))
a = np.frombuffer(input, dtype = "S1")
print("The Output is:")
print(a)
print("Type of Output is:")
print(type(a)) Output:
The type of input is: <class 'bytes'> The Output is: [b'W' b'e' b'l' b'c' b'o' b'm' b'e' b' ' b't' b'o' b' ' b'S' b'h' b'i' b's' b'h' b'i' b'r' b'K' b'a' b'g' b'n' b't' b'!' b'!' b'!' b'I' b't' b' ' b'i' b's' b' ' b'a' b' ' b'b' b'e' b's' b't' b' ' b'p' b'l' b'a' b'c' b'e' b' ' b'f' b'o' b'r' b' ' b'y' b'o' b'u' b' ' b't' b'o' b' ' b'l' b'e' b'a' b'r' b'n' b' ' b'c' b'o' b'd' b'i' b'n' b'g' b' ' b'o' b'n' b'l' b'i' b'n' b'e' b'.' b'.'] Type of Output is: <class 'numpy.ndarray'>
